Methods and apparatus to dynamically generate audio signatures adaptive to circumstances associated with media being monitored

ABSTRACT

Methods and apparatus to dynamically generate audio signatures adaptive to circumstances associated with media being monitored are disclosed. An example apparatus includes a signal selector to select a first signature scheme from among a plurality of signature schemes to generate monitored signatures for media being monitored by a meter. The first signature scheme is selected based on a circumstance associated with the media. The apparatus includes a signal generator to generate a first monitored signature from the media based on the first signature scheme. The apparatus further includes a communications interface to transmit the first monitored signature to a data collection facility.

FIELD OF THE DISCLOSURE

This disclosure relates generally to media monitoring, and, moreparticularly, to methods and apparatus to dynamically generate audiosignatures adaptive to circumstances associated with media beingmonitored.

BACKGROUND

Identifying media information and, more specifically, audio signals(e.g., information in audio streams) using signature matching techniquesis well established. Signatures are also equivalently known, andfrequently referred to, as fingerprints. Signature matching techniquesare often used in television and radio audience measurement applicationsand are implemented using several methods for generating and matchingsignatures. For example, an audience measurement meter may generatesignatures from media to which one or more audience members are exposed.The audience measurement meter may be a stationary meter that is setupto monitor the audio stream of a particular media presentation device(e.g., a television in the audience members' home) or may be a portablemeter that is carried by an audience member to monitor exposure to mediawherever the audience member goes. Signatures generated by an audiencemeasurement meter are representative of the media, or lack thereof,monitored by the meter, and may be sent to a central data collectionfacility for analysis.

Separate from the audience measurement meter, a reference generator maygenerate reference signatures representative of known media programsfrom known media sources (e.g., television channel, radio station, etc.that are provided within a broadcast region). The reference signaturesmay be stored at a reference site where the reference generator islocated and/or sent to a central data collection facility for storage.The central data collection facility may compare signatures reportedfrom an audience measurement meter with reference signatures collectedby one or more reference generators. When a signature generated by theaudience measurement meter is found to match a particular referencesignature, the known media program corresponding to the matchingreference signature may be identified as the media to which the audiencemembers associated with the audience measurement meter were exposed.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is an example environment including an example audiencemeasurement meter and an example data collection facility in accordancewith teachings disclosed herein.

FIG. 2 is a block diagram illustrating an example implementation of theaudience measurement meter of FIG. 1.

FIG. 3 is a block diagram illustrating an example implementation of thedata collection facility of FIG. 1.

FIGS. 4 and 5 are flowcharts representative of example machine readableinstructions that may be executed to implement the audience measurementmeter of FIGS. 1 and/or 2.

FIG. 6 is a flowchart representative of example machine readableinstructions that may be executed to implement the data collectionfacility of FIGS. 1 and/or 3.

FIG. 7 is a block diagram of an example processor platform structured toexecute the instructions of FIGS. 4 and/or 5 to implement the audiencemeasurement meter of FIGS. 1 and/or 2.

FIG. 8 is a block diagram of an example processor platform structured toexecute the instructions of FIG. 6 to implement the data collectionfacility of FIGS. 1 and/or 3.

DETAILED DESCRIPTION

Examples disclosed herein enable the dynamic selection of a particularsignature scheme or methodology to use for media being monitored from aplurality of available alternatives in substantially real time based ondetected circumstances associated with the media. In some examples, thesignature scheme may be selected based on characteristics or conditionsof the environment in which the media is detected and/or based oncharacteristics of the media itself. For example, one signature schememay be selected for use in relatively low noise environments, whereas asecond, different signature scheme may be selected for use whenrelatively high levels of background noise are detected. Additionally oralternatively, one signature scheme may be selected when the media isdetermined to contain predominantly speech-based audio or other audio inrelatively low frequency ranges, whereas a second, different scheme maybe selected for media containing rich content and/or audio in relativelyhigh frequency ranges, such as, for example, music. The dynamicselection of different signature schemes to be applied at any givenmoment based on the content of the media and/or the context in which itis being monitored enables the collection of signatures that are morereliable and likely to match with reference signatures, therebyincreasing the accuracy of audience measurements based on the signaturematching. While such accuracy can be achieved by collecting multiplesignatures concurrently using multiple different signature schemes,examples disclosed herein achieve similar accuracy with greaterprocessor efficiency by identifying and implementing a single particularsignature scheme at any particular moment without implementing othersignature schemes. In this manner, efficiency is increased by limitingthe number of signature schemes used at any given moment to one whilealso maintaining a high probability of an eventual match with referencesignatures. In other examples, more than one signature scheme, but fewerthan all available signature schemes, may be used at a particular pointin time.

FIG. 1 is an example environment 100 in which teachings disclosed hereinmay be implemented. The environment 100 of FIG. 1 includes one or moremedia provider(s) 102 that provide media (e.g., television programming,on-demand media, Internet-based streaming media, advertisements, music,etc.) to one or more example reference sites 104 and one or more examplemonitored sites 106. As shown in the illustrated example, the referencesite 104 is associated with and/or managed by an example audiencemeasurement entity (AME) 108, such as The Nielsen Company (US), LLC, tocollect reference media data for use in implementing various audiencemeasurement endeavors.

In some examples, the reference site 104 includes an example receiver110 (e.g., set-top boxes or the like) that receives media from the mediaprovider 102 and transmits the media to an example reference generator112 for processing. In the illustrated example, the receiver 110 istuned to a known (e.g., designated by the AME 108) channel or stationassociated with the media provider 102. By designating the station orchannel in this manner, the AME 108 can collect reference media data forthe particular station or channel that can then be used to detect themedia to which panelists are exposed (e.g., at the monitored site 106)to generate audience measurement metrics. As described more fully below,the reference media data may include reference signatures generated fromthe media received by the receiver 110. In some examples, the collectedreference signatures may be stored locally at the reference site 104along with the relevant media identifying information. Additionally oralternatively, the reference generator 112 may transmit the referencesignatures and the associated media identifying information(collectively referred to as reference media data) to a central datacollection facility 118 associated with the AME 108.

In some examples, the reference site 104 may include multiple receivers110 tuned to different channels (associated with the same and/ordifferent media provider(s) 102). In some such examples, each receivermay also have a corresponding reference generator 112. In otherexamples, a single reference generator 112 may collect and/or processthe data from more than one receiver 110. Further, in some examples,there may be multiple media monitoring reference sites each with one ormore receivers 110 and/or one or more reference generators 112. In someexamples, the AME 108 may establish remote media monitoring sites atdifferent geographic locations corresponding to regions where affiliatedstations broadcast media for the region (e.g., local televisionprogramming, local radio programming, etc.). For purposes of clarity, inthe illustrated example, one reference site 104 is shown containing onereceiver 110 tuned to a particular station or channel associated withone media provider 102.

The AME 108 enlists panelists who consent to having the AME 108 collectaudience measurement data from them that is indicative of the media towhich the panelists are exposed. In the illustrated example, themonitored site 106 corresponds to a household of an audience member whohas enrolled as a panelist in an audience measurement panel maintainedby the AME 108. Thus, as shown in the illustrated example, the monitoredsite 106 includes an example audience measurement meter 114 provided bythe AME 108 that monitors media from the media provider 102 that isplayed on an example media presentation device 116. The mediapresentation device 116 may be any type of media presentation device,such as a television, a computer, a smart phone, a tablet, a radio, etc.In some examples, the audience measurement meter 114 is integral (e.g.,by way of software, firmware, and/or hardware) with the mediapresentation device 116. In other examples, the audience measurementmeter 114 is implemented in a device separate from the mediapresentation device 116. In some examples, the audience measurementmeter 114 is a people meter that is capable of detecting and/orotherwise tracking the presence of people in the environment surroundingthe media presentation device 116 to properly credit or countindividuals as audience members exposed to media playing on the device116. Although the monitored site 106 is described above as correspondingto a panelist household, the monitored site may be any other location inwhich a panelist may be exposed to media. For instance, in someexamples, the audience measurement meter 114 is a portable meter that iscarried by a panelist such that the monitored site may be any locationwhere a media presentation device is playing media (e.g., at a store, ina car, at a friend's house, etc.). Furthermore, although only oneaudience measurement meter 114 associated with one monitored site 106 isshown in the illustrated example, the AME 108 may collect data frommultiple monitored sites 106 via multiple audience measurement meters114.

Audience measurement data associated with audience member panelists canbe collected through the use of watermarking and/or signatures.Watermarking is a technique used to identify media such as televisionbroadcasts, radio broadcasts, advertisements (television and/or radio),downloaded media, streaming media, prepackaged media, etc. Watermarkingincludes audio watermarking and video watermarking. Existing audiowatermarking techniques identify media by embedding one or more audiocodes (e.g., one or more watermarks), such as media identifyinginformation and/or an identifier that may be mapped to media identifyinginformation (e.g., via a lookup in a media lineup table), into an audiocomponent of a media signal. Video watermarking is analogous to audiowatermarking, but the video watermark is placed in a video component ofthe media signal. In some examples, the audio or video component isselected to have a signal characteristic sufficient to hide thecorresponding audio and/or video watermark. As used herein, the terms“code” or “watermark” are used interchangeably and are defined to meanany identification information (e.g., an identifier) that may beassociated with media (e.g., a program or advertisement) for the purposeof identifying the media and/or for another purpose such as tuning(e.g., a packet identifying header). As used herein “media” refers toaudio and/or visual (still or moving) content and/or advertisements. Toidentify watermarked media, the watermark(s) are extracted and used toaccess a table of reference watermarks that are mapped to mediaidentifying information. More particularly, in some examples, theaudience measurement meter 114 detects and extracts watermarks embeddedin monitored media and transmits the watermarks along with a timestampto the data collection facility 118. The data collection facility 118then processes the collected audience measurement data to identify themedia indicated by the watermarks.

Unlike media monitoring techniques based on codes and/or watermarksincluded with and/or embedded in the monitored media, fingerprint orsignature-based media monitoring techniques generally use one or moreinherent characteristics of the monitored media during a monitoring timeinterval to generate a substantially unique proxy for the media. Such aproxy is referred to as a signature or fingerprint, and can take anyform (e.g., a series of digital values, a waveform, etc.) representativeof any aspect(s) of the media signal(s) (e.g., the audio and/or videosignals forming the media presentation being monitored). A goodsignature is one that is repeatable when processing the same mediapresentation, but that is unique relative to other (e.g., different)presentations of other (e.g., different) media. Accordingly, the term“fingerprint” and “signature” are used interchangeably herein and aredefined herein to mean a proxy for identifying media that is generatedfrom one or more inherent characteristics of the media. That is, while asingle item of signature data may correspond to a fraction of a secondof media (and, thus, unlikely sufficient to uniquely identify themedia), as used herein a signature (or fingerprint) corresponds to acontinuous stream of such individual items of signature datasufficiently long to identify the associated media relative to othermedia with a relatively high level of confidence. The particular lengthof such signatures may differ depending upon the nature of the mediaand/or the level of confidence desired.

Signature-based media monitoring generally involves determining (e.g.,generating and/or collecting) signature(s) representative of a mediasignal (e.g., an audio signal and/or a video signal) output by amonitored media device (e.g., the media presentation device 116 ofFIG. 1) and comparing the monitored signature(s) to one or morereference signatures corresponding to known (e.g., reference) mediasources. In the illustrated example, reference signatures are generatedby the reference generator 112 processing the media received by thereceiver 110. For purposes of explanation, signatures generated at areference site 104 (e.g., by the reference generator 112) are referredto herein as reference signatures. By contrast, signatures generated ata monitored site 106 (e.g., by the audience measurement meter 114) arereferred to herein as monitored signatures. The comparison of monitoredand reference signatures may be implemented at the data collectionfacility 118 based on the data received from both the referencegenerator 112 and the audience measurement meter 114.

Various comparison criteria, such as a cross-correlation value, aHamming distance, significant peaks comparison, etc., can be evaluatedto determine whether a monitored signature matches a particularreference signature. When a match between the monitored signature andone of the reference signatures is found, the monitored media can beidentified as corresponding to the particular reference mediarepresented by the reference signature that is matched with themonitored signature. Because attributes, such as an identifier of themedia, a presentation time, a broadcast channel, etc., are collected forthe reference signature, these attributes may then be associated withthe monitored media whose monitored signature matched the referencesignature. Example systems for identifying media based on codes and/orsignatures are long known and were disclosed in Thomas, U.S. Pat. No.5,481,294, which is hereby incorporated by reference in its entirety.

For monitored signatures to be compared with reference signatures, bothsets of signatures need to be generated in a consistent manner. That is,unless the configurations of the respective signature techniques orschemes used to collect both the reference and monitored signatures arethe same, the resulting signatures are unlikely to match even if theyare generated from the same piece of media. There are many factors thatgo into the configuration of a given signature scheme including, forexample, which frequency bands are analyzed, the number of bits used,the sampling frequency/rates, the duration of the sampling, etc. Theability for a given signature scheme with a given configuration toproduce signatures from different instances of the same media that canbe matched with a relatively high degree of confidence depends upon thecircumstances associated with the media and its collection. Thecircumstances that impact the effectiveness or reliability of a givensignature scheme include characteristics of the environment associatedwith the media being monitored and characteristics of the media itself.

For instance, the amount of background or ambient noise in theenvironment associated with the media being monitored can have adeleterious impact on some signature schemes while other signatureschemes can tolerate the noise and capture reliable signatures. Asanother example, different signature schemes can have different levelsof effectiveness based on characteristics of the media being monitored,such as the type of content contained in the media (e.g., the genre).For example, a relatively low frequency signature scheme may be good atgenerating signatures from media with an audio stream primarilycontaining speech (e.g., a talk show, a news show, etc.) becausespeech-based audio typically exhibits most of its signal energy atrelatively low frequencies (e.g., around 1 kHz). However, the samesignature scheme may not be as effective at generating reliablesignatures from media containing rich content, such as music, with audiospreading across a wide frequency spectrum and/or that exhibits most ofits signal energy at relatively high frequencies (e.g., above 3 or 4kHz). Conversely, a different signature scheme configured to focus onhigher frequency bands may be able to generate signatures from musicthat can be more reliably repeated than a relatively low frequencysignature scheme that may be more suitable for speech.

As the circumstances associated with media to be monitored can changeover time (either due to a change in content or due to a change inenvironmental circumstances), there may be no single configuration for agiven signature scheme that provides reliable results in everysituation. One approach to solve this issue involves implementing asignature scheme configured based on tradeoffs or compromises betweenthe advantages and disadvantages of different types of signature schemestailored to different circumstances. While this one-size-fits-allapproach may enable the collection of signatures that are reliable inmany situations, there may be times when, due to particularcircumstances, generated signatures will not be as reliable as desired.Additionally, implementing a one-size-fits-all signature scheme may alsoresult in more processing of data than is actually needed to reliablyproduce signatures. For example, the one-size-fits-all signature schememay include a relatively large payload to enable an analysis of themedia on the assumption that there will be some level of backgroundnoise. However, if there is little or no background noise in aparticular circumstance, this extra payload unnecessarily increases theprocessing requirements of the system implementing the signature scheme.Furthermore, larger payloads also increase bandwidth requirements whenthe resulting signatures are transmitted to the data collection facility118. Another approach to handle different circumstances of monitoredmedia involves the concurrent implementation of multiple signaturesschemes individually tailored to the different circumstances expectedfor the media being monitored. While this would enable more reliablesignatures to be generated based on the particular circumstance of themedia, the processing requirements and bandwidth to implement such asystem increases with each additional signature scheme included in thesystem.

In the illustrated example, the audience measurement meter 114 overcomesthe above obstacles by detecting circumstances associated with the mediato be monitored and then selecting a suitable signature scheme from aplurality of available signature schemes that is adapted or tailored tothe detected circumstances. In some examples, the audience measurementmeter 114 detects the circumstances associated with the media bycharacterizing the media based on detected characteristics of the media.In some examples, the identification of such characteristics is used toidentify the genre and/or type of content of the media (e.g., whetherthe media contains relatively sparse audio with intermittent gaps, suchas speech, or contains relatively rich content, such as music). In someexamples, the audience measurement meter 114 may further detect thenature of the environment in which the media is being monitored by, forexample, detecting an amount of background noise. Based on thecharacterization of the media and the associated environment, theaudience measurement meter 114 may select a particular signature schemeadapted to the detected content of the media. In some examples, theparticular signature scheme is dynamically changed in substantiallyreal-time as changes in the circumstances associated with the media aredetected. In this manner, a signature scheme that is adapted to thecurrent circumstances of media being monitored is used to generatesignatures, thereby increasing the likelihood that the resultingmonitored signatures will reliably match with corresponding referencesignatures while improving efficiency by using only one signature schemeat any given time that is tailored to have a payload that is no greaterthan necessary. Thus, in some examples, when one signature scheme isselected for implementation in connection with a particularcircumstance, other available signature schemes are not used.

As mentioned above, for a reliable match to be found between a monitoredsignature and a reference signature, both signatures need to begenerated using consistent signature schemes. In some examples, thereference generator 112 may dynamically adapt the signature scheme usedto generate reference signatures in a similar manner to the audiencemeasurement meter 114 so that both the reference generator 112 and theaudience measurement meter 114 are using the same scheme under the samecircumstances. While this approach may work for circumstances based onthe characteristics or content of the media, the reference generator 112may be unable to determine the environmental conditions associated withthe media monitored by the audience measurement meter 114. Accordingly,in some examples, the reference generator 112 concurrently implementsmultiple signature schemes according to the different environmentalconditions anticipated for the audience measurement meter 114. In someexamples, the reference generator 112 implements all pre-definedsignature scheme concurrently to generate reference signatures for eachavailable (pre-defined) signature scheme. For example, the referencegenerator 112 may implement a first signature scheme that isspecifically adapted to a low noise environment (e.g., noise below athreshold level) and separately implement a second signature scheme thatis adapted to a high noise environment (e.g., noise above a thresholdlevel). The signatures collected using each different signature schememay be stored in separate reference libraries or databases and/orotherwise catalogues for future reference. In this manner, regardless ofwhether the environment associated with media monitored by the audiencemeasurement meter 114 is above or below the noise threshold (therebychanging the signature scheme used to generate monitored signatures),the reference generator 112 will collect suitable reference signaturesfor comparison to the monitored signatures.

Although the reference generator 112 may dynamically select signatureschemes based on the characteristics of the media (e.g., speech versusmusic) as mentioned above, the reference generator 112 may neverthelessimplement separate signature schemes for each different type (orcharacteristic) of media expected so that a complete database ofreference signatures corresponding to each signature scheme may becreated. In this manner, there is little risk that a monitored signaturereported by the audience measurement meter 114 will not match with acorresponding reference signature in at least one of the scheme-specificdatabases.

FIG. 2 is a block diagram illustrating an example implementation of theaudience measurement meter 114 of FIG. 1. As shown in the illustratedexample of FIG. 2, the audience measurement meter 114 includes anexample media detector 202, an example media environment analyzer 204,an example media content analyzer 206, an example signature schemeselector 208, an example signature scheme database 210, an examplesignature generator 212, and an example communications interface 214.

The example media detector 202 of FIG. 2 enables the audiencemeasurement meter 114 to detect and/or monitor media. In some examples,the media detector 202 monitors an audio stream of media. In suchexamples, the media detector 202 includes or is otherwise associatedwith an audio sensor such as, for example, a microphone, an audio inputconnection, etc. Additionally or alternatively, in some examples, themedia detector 202 may be a video stream of the media and, as such,includes or is otherwise associated with a video sensor, such as, forexample, a camera, a video input connection, etc.

In some examples, the media detector 202 may detect ambient noiseunrelated to the audio stream and/or video stream of media to bemonitored. Accordingly, in some examples, the audience measurement meter114 is provided with the example media environment analyzer 204 toanalyze the media detected by the media detector 202 to determine thecircumstances associated with the environment in which the media isdetected, including whether there is background noise and/or the amountof background noise. In some examples, the media environment analyzer204 determines the amount of noise based on watermarks detected in themedia. In some examples, the media content analyzer 206 detects and/orextracts such watermarks from the media. As described above, watermarksinclude media identifying information that is encoded into the mediathat is received at a media presentation device (e.g., the mediapresentation device 116). As the nature of the watermarks are known inadvance, the detection of the watermarks relative to all audio that isdetected in a particular environment may be analyzed to calculate thesignal to noise ratio for the media relatively accurately. By analyzingthe signal to noise ratio over time, the amount of background noise tothe audio stream of the media may be quantified. In some instances,media being monitored may not have watermarks embedded therein. In suchexamples, the media environment analyzer 204 may use any other suitablemethodology to estimate the presence and/or amount of background noise.While some such approaches may not be as deterministic or reliable aswhen the analysis is based on watermarks, such approaches are likely todistinguish between a relatively high background noise environment(e.g., noise above a noise threshold) and a relatively low backgroundnoise environment (e.g., noise below the noise threshold) under mostcircumstances. In some examples, analysis of signals that containwatermarks may be used as input to machine learning models implementedto predict the amount of background noise associated with signals thatdo not include watermarks.

In some examples, the media environment analyzer 204 may also processthe audio detected by the media detector 202 for further analysis. Inparticular, in some examples, when a high noise environment (e.g.,background noise that exceeds a noise threshold) is detected based onwatermarks, the media environment analyzer 204 may process the audio,based on the detected watermarks, to filter out at least some of thebackground noise to isolate the audio stream of the media. In someexamples, the media environment analyzer 204 may perform similarprocesses on a video stream detected by the media detector 202.

In the illustrated example of FIG. 2, the audience measurement meter 114is provided with the example media content analyzer 206 to detectcircumstances associated with the media detected by the media detector202. More particularly, the circumstances associated with the mediadetected by the media content analyzer 206 pertain to the content of themedia. Thus, the media environment analyzer 204 and the media contentanalyzer 206 collectively operate to determine the circumstancesassociated with the media, with the media environment analyzer 204detecting characteristics of the environment of the media while themedia content analyzer 206 detects characteristics of the media itself.In some examples, the characteristics of the media detected by the mediacontent analyzer 206 are used to characterize the media by determiningthe genre or type of media detected. For example, the media contentanalyzer 206 may characterize particular media as primarily speech-basedor primarily music-based. In some examples, this determination is basedon where on the frequency spectrum a majority of the signal energy islocated. In other examples, the characteristics of the media identifiedby media content analyzer 206 may be more generic to characterize themedia without specifically identifying the genre or type of mediadetected. For example, the media content analyzer 206 may characterizethe media directly based on where on the frequency spectrum a majorityof the signal energy is located (e.g., skewed to a relatively lowfrequency band (e.g., around 1 kHz) or to a relatively high frequencyband (e.g., above 3 or 4 kHz)). Additionally or alternatively, the mediacontent analyzer 206 may determine how widespread the energy signal ison the frequency spectrum (e.g., the spectral frequency density). Insome examples, other characteristics of the media may also be identifiedsuch as, for example, the timing, amount, and/or amplitude of peaks inthe media signal.

In some examples, the media content analyzer 206 analyzes the media todetect or extract watermarks embedded in the media. Such watermarks maybe used to identify the media and, thus, determine the genre and/or typeof media detected, and/or other known characteristics of the media.Additionally or alternatively, such watermarks may be used to identify abaseline from which the media environment analyzer 204 may calculate theamount of background noise as described above.

The example signature scheme selector 208 of FIG. 2 selects one ofmultiple different signature schemes available for implementation togenerate signatures from the monitored media. In the illustratedexample, the different signature schemes are made available forselection by the signature scheme selector 208 by storing machinereadable instructions associated with the different signatures, alongwith the relevant configuration parameters, in the signature schemedatabase 210.

In some examples, the different signature schemes are configured orotherwise customized to achieve a desired quality and/or improve thequality (e.g., reliability, uniqueness, repeatability, etc.) ofsignatures of the media being monitored depending on the circumstancesassociated with the media. That is, different signature schemes may beconfigured or otherwise customized to achieve a desired quality and/orimprove (e.g., optimize) the collection of signatures from differenttypes of media (e.g., speech versus music) and/or under differentenvironmental conditions (e.g., low background noise versus highbackground noise).

For example, a first signature scheme may be specifically adapted orotherwise customized to generate signatures from media with audio signalenergy predominately in relatively low frequency bands (often associatedwith speech content) while a second signature scheme may be specificallyadapted or otherwise customized to generate signatures from media withaudio signal energy predominately in relatively high frequency bands(often associated with music). In some examples, whether media ischaracterized as low frequency media or high frequency media may bedefined by a particular frequency threshold defining the boundarybetween the low and high frequency bands. In some examples, thefrequency band for low frequency signals may be defined independent ofthe frequency band for high frequency signals. In some examples, theremay be additional signature schemes specifically adapted or otherwisecustomized to intermediate frequency bands between high and low bands.In some examples, the frequency bands to which the different signatureschemes are focused may be mutually exclusive without any overlap. Inother examples, different ones of the signature schemes may haveoverlapping frequency bands. In some examples, a first signature schememay be adapted or otherwise customized to focus on a relatively narrowfrequency band while a second signature scheme is adapted or otherwisecustomized to generate signatures from media with audio signals spreadacross a relatively wide frequency band.

While the above examples of different signature schemes are defined withrespect to their associated frequency bands of interest, other signatureschemes may be configured based on other aspects of the media inaddition to or instead of frequency. For example, some signature schemesmay also consider peaks in the monitored signal relative to changes infrequency band. As another example, signature schemes may be based ondifferences in time domain rather than the frequency domain.Additionally or alternatively, some signature schemes may be adapted toenhance (e.g., optimize) signature generation when there is a relativelyhigh level of background noise while other signature schemes are adaptedfor low levels of background noise. For example, signature schemes forrelatively high noise environments may include higher sampling ratesand/or samples extending for longer durations than signature schemesused in a relatively low noise environment. In some examples, whetherthe media environment is characterized as containing high or low levelsof noise may be defined by a particular noise threshold demarcating thedifferent circumstances. In some examples, there may be additionalsignature schemes specifically adapted to intermediate levels of noise.That is, different signature schemes may be selected based on whetherdifferent noise thresholds are exceeded.

In some examples, different signature schemes may be based on acombination of multiple factors outlined above in a manner that tailorsthe different signature schemes to different circumstances. As a oneexample, four different signature schemes may include (1) a lowfrequency media content, low noise signature scheme, (2) a low frequencymedia content, high noise signature scheme, (3) a high frequency mediacontent, low noise signature scheme, and (4) a high frequency mediacontent, high noise signature scheme. In such examples, the signaturescheme selector 208 selects a particular one of the signature schemesbased on the current circumstances of the media being monitored(characteristics of the media and/or the associated environment) asdetermined by the media environment analyzer 204 and/or the mediacontent analyzer 206. In some examples, the signature scheme selector208 may dynamically change the selected signature scheme insubstantially real time to adapt to changes in the media content and/orenvironment. For example, if the media is music on a radio, thesignature scheme selector 208 may select a relatively high frequencysignature scheme that is adapted to the typical frequency rangesexpected for music and then switch to a lower frequency signature schememore fitting for speech when the audio stream switches to a speech-basedadvertisement. Further, the signature scheme selector 208 may selectsignature schemes adapted to relatively high noise environments whensuch environments are detected (e.g., in a vehicle or where there is acrowd of people making noise in addition to the media) and switch toother signature schemes when little or no background noise is detected(e.g., in the privacy of an audience member's home).

While frequency bands and noise (or any other factor(s)) may be combinedto select a particular signature scheme at any given moment, in otherexamples, signature schemes may be tailored to a single factorindependent of the others. For example, three different signatureschemes may include (1) a low frequency signature scheme, (2) a highfrequency signature scheme, and (3) a high noise signature scheme. Inthis example, when the media environment analyzer 204 detects a lownoise environment (e.g., noise levels are below a noise threshold), thesignature scheme selector 208 selects either the low frequency signaturescheme or the high frequency signature scheme depending on the contentof the media as determined by the media content analyzer 206. However,if the media environment analyzer 204 determines that the noise levelexceeds a noise threshold, the signature scheme selector 208 selects thehigh noise signature scheme regardless of the characteristics of themedia.

The example signature generator 212 uses whichever signature scheme isselected by the signature scheme selector 208 to generate signatures ofthe media being monitored. Because the signature scheme being applied atany given moment is selected based on the circumstances of the media(e.g., content characteristics and/or environmental conditions), it islikely that the signatures will be reliable to match against referencesignatures generated by the reference generator 112 using the samesignature scheme. Such a match is possible because the referencegenerator 112 of FIG. 1 generates signatures based on each of thesignature schemes available to the audience measurement meter 114 (e.g.,stored in the signature scheme database 210). In some examples, thereference generator 112 implements all of the signature schemesconcurrently to generate a complete library of reference signatures forthe relevant media using each of the signature schemes. Unlike thereference generator 112, in some examples, the example signaturegenerator 212 of FIG. 2 implements only one signature scheme at anygiven time without implementing other signature schemes that may beavailable in the signature scheme database 210. This can significantlyimprove the processor efficiencies of the audience measurement meterbecause such an approach enables the capture of reliable signaturesunder virtually any circumstance while eliminating the need to implementmultiple different signature schemes concurrently.

In some examples, the signature generator 212 also generates metadatafor each signature generated. The metadata includes a scheme identifierthat indicates the particular signature scheme used to generate thecorresponding signature. In some examples, the scheme identifierincludes, for example, a numeric identifier to identify the selectedsignature scheme or algorithm, a second numeric identifier to identify aparticular configuration of the selected signature algorithm, etc. Boththe signature and the scheme identifier generated by the signaturegenerator 212 (collectively referred to as audience measurement data)may be transmitted, via the communications interface 214, to the datacollection facility 118 of FIG. 1 for further processing. In some suchexamples, as described more fully below, the data collection facility118 uses the scheme identifier to determine the appropriate library ofreference signatures with which to compare the reported signature.

While an example manner of implementing the example audience measurementmeter 114 of FIG. 1 is illustrated in FIG. 2, one or more of theelements, processes and/or devices illustrated in FIG. 2 may becombined, divided, re-arranged, omitted, eliminated and/or implementedin any other way. Further, the example media detector 202, the examplemedia environment analyzer 204, the example media content analyzer 206,the example signature scheme selector 208, the example signature schemedatabase 210, the example signature generator 212, the examplecommunications interface 214 and/or, more generally, the exampleaudience measurement meter 114 of FIG. 2 may be implemented by hardware,software, firmware and/or any combination of hardware, software and/orfirmware. Thus, for example, any of the example media detector 202, theexample media environment analyzer 204, the example media contentanalyzer 206, the example signature scheme selector 208, the examplesignature scheme database 210, the example signature generator 212, theexample communications interface 214 and/or, more generally, the exampleaudience measurement meter 114 could be implemented by one or moreanalog or digital circuit(s), logic circuits, programmable processor(s),programmable controller(s), graphics processing unit(s) (GPU(s)),digital signal processor(s) (DSP(s)), application specific integratedcircuit(s) (ASIC(s)), programmable logic device(s) (PLD(s)) and/or fieldprogrammable logic device(s) (FPLD(s)). When reading any of theapparatus or system claims of this patent to cover a purely softwareand/or firmware implementation, at least one of the example mediadetector 202, the example media environment analyzer 204, the examplemedia content analyzer 206, the example signature scheme selector 208,the example signature scheme database 210, the example signaturegenerator 212, and/or the example communications interface 214 is/arehereby expressly defined to include a non-transitory computer readablestorage device or storage disk such as a memory, a digital versatiledisk (DVD), a compact disk (CD), a Blu-ray disk, etc. including thesoftware and/or firmware. Further still, the example audiencemeasurement meter 114 of FIG. 1 may include one or more elements,processes and/or devices in addition to, or instead of, thoseillustrated in FIG. 2, and/or may include more than one of any or all ofthe illustrated elements, processes and devices. As used herein, thephrase “in communication,” including variations thereof, encompassesdirect communication and/or indirect communication through one or moreintermediary components, and does not require direct physical (e.g.,wired) communication and/or constant communication, but ratheradditionally includes selective communication at periodic intervals,scheduled intervals, aperiodic intervals, and/or one-time events.

FIG. 3 is a block diagram illustrating an example implementation of thedata collection facility 118 of FIG. 1. As shown in the illustratedexample of FIG. 3, the data collection facility 118 includes an examplecommunications interface 302, an example audience measurement database304, an example reference signature database 306, an example monitoredsignature analyzer 308, and an example signature comparator 310.

In the illustrated example, the communications interface 302 receivesaudience measurement data, including monitored signatures and associatedscheme identifiers, as reported from various audience measurement meters(e.g., the audience measurement meter 114). Such audience measurementdata may be stored in the audience measurement database 304.Additionally, in some examples, the communications interface 302receives reference media data, including reference signatures andassociated media identifying information, collected from variousreference generators (e.g., the reference generator 112). In someexamples, the reference generator 112 may provide scheme identifierssimilar to the audience measurement meter 114 to designate theparticular signature scheme used to generate each reported referencesignature. In other examples, scheme identifiers are not collected withthe reference signatures because the reference generator 112 does notswitch between different signature schemes but continuously reportssignatures generated based on each relevant scheme. With thetransmission of reference signatures dedicated to a particular signaturescheme, the data collection facility 118 may be enabled to properlyassociate the reference signatures with the relevant signature schemewithout needing to collect a scheme identifier.

As mentioned above, the reference generator 112 may transmit mediaidentifying information along with the reported reference signatures.The media identifying information is associated with the referencesignatures to enable the identification of the media from which thereference signatures were created. In some examples, the referencesignatures and the associated media identifying information obtainedfrom the reference generator 112 are stored in the reference signaturedatabase 306. In some examples, the reference signatures are grouped ororganized into separate libraries of reference signatures associatedwith each different signature scheme used to collect the signatures. Insome examples, each type of reference signature (e.g., based on adifferent signature scheme) may be stored in a separate database. Insome examples, the reference signature database 306 is implemented witha distributed computing architecture that includes clusters of nodes. Insome such examples, each different scheme may be associated with aseparate cluster of nodes. Additionally or alternatively, as representedin FIG. 3, the reference signatures may be stored in a single databasebut distinguished based on a tag or identifier stored in connection witheach type of reference signature.

In the illustrated example, the monitored signature analyzer 308analyzes the monitored signatures and associated scheme identifiersreported from the audience measurement meter 114 for subsequentprocessing. For example, the monitored signature analyzer 308 identifiesthe particular signature scheme used to generate the signature based onthe associated scheme identifier. Based on this information, the examplesignature comparator 310 compares the monitored signatures to thecorresponding library of reference signatures associated with the samesignature scheme. In some examples, monitored signatures may not includescheme identifiers and/or the data collection facility 118 may not usethe scheme identifiers. In such examples, the monitored signatureanalyzer 308 compares the monitored signatures against the variousdifferent types of reference signatures to identify the best match. Oncea match is identified, the example monitored signature analyzer 308associates the monitored signature to the media identifying informationcorresponding to the matching reference signature. In this manner, theAME 108 is able to determine the media to which an audience memberassociated with the audience measurement meter 114 was exposed.

While an example manner of implementing the example data collectionfacility 118 of FIG. 1 is illustrated in FIG. 3, one or more of theelements, processes and/or devices illustrated in FIG. 3 may becombined, divided, re-arranged, omitted, eliminated and/or implementedin any other way. Further, the example communications interface 302, theexample audience measurement database 304, the example referencesignature database 306, the example monitored signature analyzer 308,the example signature comparator 310 and/or, more generally, the exampledata collection facility 118 of FIG. 3 may be implemented by hardware,software, firmware and/or any combination of hardware, software and/orfirmware. Thus, for example, any of the example communications interface302, the example audience measurement database 304, the examplereference signature database 306, the example monitored signatureanalyzer 308, the example signature comparator 310 and/or, moregenerally, the example data collection facility 118 could be implementedby one or more analog or digital circuit(s), logic circuits,programmable processor(s), programmable controller(s), graphicsprocessing unit(s) (GPU(s)), digital signal processor(s) (DSP(s)),application specific integrated circuit(s) (ASIC(s)), programmable logicdevice(s) (PLD(s)) and/or field programmable logic device(s) (FPLD(s)).When reading any of the apparatus or system claims of this patent tocover a purely software and/or firmware implementation, at least one ofthe example communications interface 302, the example audiencemeasurement database 304, the example reference signature database 306,the example monitored signature analyzer 308, and/or the examplesignature comparator 310 is/are hereby expressly defined to include anon-transitory computer readable storage device or storage disk such asa memory, a digital versatile disk (DVD), a compact disk (CD), a Blu-raydisk, etc. including the software and/or firmware. Further still, theexample data collection facility 118 of FIG. 1 may include one or moreelements, processes and/or devices in addition to, or instead of, thoseillustrated in FIG. 3, and/or may include more than one of any or all ofthe illustrated elements, processes and devices.

Flowcharts representative of example hardware logic, machine readableinstructions, hardware implemented state machines, and/or anycombination thereof for implementing the audience measurement meter 114of FIGS. 1 and/or 2 is shown in FIGS. 4 and 5. Further, a flowchartrepresentative of example hardware logic, machine readable instructions,hardware implemented state machines, and/or any combination thereof forimplementing the data collection facility 118 of FIGS. 1 and/or 3 isshown in FIG. 6. The machine readable instructions may be an executableprogram or portion of an executable program for execution by a computerprocessor such as the processors 712, 812 shown in the example processorplatforms 700, 800 discussed below in connection with FIGS. 7 and 8. Theprograms may be embodied in software stored on a non-transitory computerreadable storage medium such as a CD-ROM, a floppy disk, a hard drive, aDVD, a Blu-ray disk, or a memory associated with the processor 712, 812,but the entire program and/or parts thereof could alternatively beexecuted by a device other than the processor 712, 812 and/or embodiedin firmware or dedicated hardware. Further, although the exampleprograms are described with reference to the flowcharts illustrated inFIGS. 4-6, many other methods of implementing the example audiencemeasurement meter 114 and/or the example data collection facility 118may alternatively be used. For example, the order of execution of theblocks may be changed, and/or some of the blocks described may bechanged, eliminated, or combined. Additionally or alternatively, any orall of the blocks may be implemented by one or more hardware circuits(e.g., discrete and/or integrated analog and/or digital circuitry, anFPGA, an ASIC, a comparator, an operational-amplifier (op-amp), a logiccircuit, etc.) structured to perform the corresponding operation withoutexecuting software or firmware.

As mentioned above, the example processes of FIGS. 4-6 may beimplemented using executable instructions (e.g., computer and/or machinereadable instructions) stored on a non-transitory computer and/ormachine readable medium such as a hard disk drive, a flash memory, aread-only memory, a compact disk, a digital versatile disk, a cache, arandom-access memory and/or any other storage device or storage disk inwhich information is stored for any duration (e.g., for extended timeperiods, permanently, for brief instances, for temporarily buffering,and/or for caching of the information). As used herein, the termnon-transitory computer readable medium is expressly defined to includeany type of computer readable storage device and/or storage disk and toexclude propagating signals and to exclude transmission media.

“Including” and “comprising” (and all forms and tenses thereof) are usedherein to be open ended terms. Thus, whenever a claim employs any formof “include” or “comprise” (e.g., comprises, includes, comprising,including, having, etc.) as a preamble or within a claim recitation ofany kind, it is to be understood that additional elements, terms, etc.may be present without falling outside the scope of the correspondingclaim or recitation. As used herein, when the phrase “at least” is usedas the transition term in, for example, a preamble of a claim, it isopen-ended in the same manner as the term “comprising” and “including”are open ended. The term “and/or” when used, for example, in a form suchas A, B, and/or C refers to any combination or subset of A, B, C such as(1) A alone, (2) B alone, (3) C alone, (4) A with B, (5) A with C, (6) Bwith C, and (7) A with B and with C.

Turning in detail to the flowcharts, FIG. 4 represents example machinereadable instructions that may be executed to implement the audiencemeasurement meter 114 of FIGS. 1 and/or 2. The program of FIG. 4 beginsat block 402 where the example media detector 202 monitors audioassociated with media to be monitored. At block 404, the example mediaenvironment analyzer 204 and/or the example media content analyzer 206detect circumstances associated with the media based on the audio. Forexample, the media environment analyzer 204 may detect the circumstancesof the surrounding environment such as, for example, the level ofbackground noise to the audio stream of the media. The media contentanalyzer 206 may detect characteristics of the media itself. In someexamples, the media content analyzer 206 uses such media characteristicsto characterize the media as corresponding to a particular genre or typeof media content.

At block 406, the example media environment analyzer 204 and/or theexample media content analyzer 206 determines whether the detectedcircumstance associated with the media has changed. If so, at block 408,the example signature scheme selector 208 selects a signature schemeadapted or otherwise customized to the newly detected circumstance.Thereafter, at block 410, the example signature generator 212 generatesa monitored signature from the media using the currently selectedsignature scheme (e.g., selected at block 408). Returning to block 406,if the detected circumstance associated with the media has not changed(e.g., after at least one iteration of the example process without achange), control advances directly to block 410.

At block 412, the example signature generator 212 generates a schemeidentifier for the monitored signature. The scheme identifier serves toidentify the signature scheme used to generate the associated monitoredsignature. At block 414, the communications interface 214 determineswhether to transmit audience measurement data to the data collectionfacility 118. In some examples, audience measurement data is transmittedas soon as it is created. In other examples, audience measurement datamay be aggregated over time and then transmitted at periodic oraperiodic intervals. That is, in some examples, each monitored signaturemay be independently reported to the data collection facility 118. Inother examples, multiple monitored signatures may be collected andcommunicated to the data collection facility 118 in a singletransmission. Thus, if the communications interface 214 determines totransmit the audience measurement data (block 414), control advances toblock 416 where the communications interface 214 transmits the monitoredsignature along with the scheme identifier. If the communicationsinterface 214 determine not to transmit the audience measurement data(block 414), block 416 is skipped. At block 418, the example audiencemeasurement meter 114 determines whether to continue. If so, controlreturns to block 402 to repeat the process. Otherwise, the exampleprocess of FIG. 4 ends.

FIG. 5 represents example machine readable instructions that may beexecuted to implement the audience measurement meter 114 of FIGS. 1and/or 2. The program of FIG. 5 begins at block 502 where the examplemedia detector 202 monitors audio associated with media to be monitored.At block 504, the example media content analyzer 206 determines whetherwatermarks are embedded in the media. If so, at block 506, the examplemedia environment analyzer 204 calculates the level of background noisebased on the watermarks. Thereafter, the example media environmentanalyzer 204 isolates the audio stream of the media from the backgroundnoise before advancing to block 512. Returning to block 504, if theexample media content analyzer 206 determines there are no watermarksembedded in the media, control advances to block 510 where the examplemedia environment analyzer 204 estimates the level of background noisewithout the watermarks. In some examples, without the deterministicinput of embedded watermarks, it may not be possible to isolate theaudio stream of the media from background noise. Accordingly, controladvances directly block 512 after estimating the level of backgroundnoise at block 510.

At block 512, the example media environment analyzer 204 determineswhether the level of background noise exceeds a noise threshold. If so,control advances to block 514 where the example media content analyzer206 characterizes the audio stream. Thereafter, at block 516, theexample signature scheme selector 208 selects a signature scheme for ahigh noise environment based on the characterization. As outlined above,the audio stream may be isolated from background noise (block 508) ifwatermarks were included in the media or may not be isolated from thebackground noise. In either case, the example media content analyzer 206characterizes the audio stream by identifying one or morecharacteristics associated with the audio being monitored to facilitatethe selection of the signature scheme. While the characterization of theisolated audio stream is likely to be more accurate, it is expected thatthe characterization of the non-isolated audio stream will stillfacilitate the selection of a signature scheme under most circumstances.Once the signature scheme is selected (block 516), control advances toblock 522 where the example signature generator 212 generates asignature from the media using the selected signature scheme.

Returning to block 512, if the level of background noise does not exceedthe threshold, control advances to block 518 where the example mediacontent analyzer 206 characterizes the audio stream. As with block 514,the characterization of the audio stream at block 518 may be based onthe isolated audio stream or the non-isolated audio stream. At block520, the example signature scheme selector 208 selects a signaturescheme for a low noise environment based on the characterization.Thereafter, control advances to block 522 to generate a signature fromthe media using the selected signature scheme.

At block 524, the example signature generator 212 generates a schemeidentifier for the signature. The scheme identifier serves to identifythe signature scheme used to generate the associated signature. At block526, the communications interface 214 determines whether to transmitaudience measurement data to the data collection facility 118. If so,control advances to block 528 where the communications interface 214transmits the signature along with the scheme identifier. If thecommunications interface 214 determines not to transmit the audiencemeasurement data (block 526), block 528 is skipped. At block 530, theexample audience measurement meter 114 determines whether to continue.If so, control returns to block 502 to repeat the process. Otherwise,the example process of FIG. 5 ends.

FIG. 6 represents example machine readable instructions that may beexecuted to implement the data collection facility 118 of FIGS. 1 and/or3. The program of FIG. 6 begins at block 602 where the examplecommunications interface 302 receives reference media data from thereference generator 112 collected using multiple different signatureschemes. At block 604, the example reference signature database 306stores reference signatures and associated media identifying informationfrom the reference media data organized based on the different signatureschemes. At block 606, the example communications interface 302 receivesaudience measurement data from an audience measurement meter 114. Theaudience measurement data includes monitored signatures and associatedscheme identifiers.

At block 608, the example monitored signature analyzer 308 identifiessignature scheme used to generate a monitored signature based on anassociated scheme identifier reported in the audience measurement data.At block 610, the example signature comparator 310 compares themonitored signature to reference signatures corresponding to theidentified signature scheme. At block 612, the example signaturecomparator 310 determines whether the monitored signature matches areference signature. If so, at block 614, the monitored signatureanalyzer 308 associates the media identifying information for thematching reference signature with the monitored signature. If there isno match at block 612, block 614 is skipped. At block 616, the monitoredsignature analyzer 308 determines whether there is another monitoredsignature. If so, control returns to block 608. Otherwise, controladvances to block 618 where the data collection facility 118 determineswhether to continue. If so, control returns to block 602. Otherwise, theexample process of FIG. 6 ends.

FIG. 7 is a block diagram of an example processor platform 700structured to execute the instructions of FIGS. 4 and/or 5 to implementthe audience measurement meter 114 of FIGS. 1 and/or 2. The processorplatform 700 can be, for example, a server, a personal computer, aworkstation, a self-learning machine (e.g., a neural network), a mobiledevice (e.g., a cell phone, a smart phone, a tablet such as an iPad™), apersonal digital assistant (PDA), an Internet appliance, a DVD player, aCD player, a digital video recorder, a Blu-ray player, a gaming console,a personal video recorder, a set top box, a headset or other wearabledevice, or any other type of computing device.

The processor platform 700 of the illustrated example includes aprocessor 712. The processor 712 of the illustrated example is hardware.For example, the processor 712 can be implemented by one or moreintegrated circuits, logic circuits, microprocessors, GPUs, DSPs, orcontrollers from any desired family or manufacturer. The hardwareprocessor may be a semiconductor based (e.g., silicon based) device. Inthis example, the processor implements the example media detector 202,the example media environment analyzer 204, the example media contentanalyzer 206, the example signature scheme selector 208, the examplesignature generator 212, and the example communications interface 214.

The processor 712 of the illustrated example includes a local memory 713(e.g., a cache). The processor 712 of the illustrated example is incommunication with a main memory including a volatile memory 714 and anon-volatile memory 716 via a bus 718. The volatile memory 714 may beimplemented by Synchronous Dynamic Random Access Memory (SDRAM), DynamicRandom Access Memory (DRAM), RAMBUS® Dynamic Random Access Memory(RDRAM®) and/or any other type of random access memory device. Thenon-volatile memory 716 may be implemented by flash memory and/or anyother desired type of memory device. Access to the main memory 714, 716is controlled by a memory controller.

The processor platform 700 of the illustrated example also includes aninterface circuit 720. The interface circuit 720 may be implemented byany type of interface standard, such as an Ethernet interface, auniversal serial bus (USB), a Bluetooth® interface, a near fieldcommunication (NFC) interface, and/or a PCI express interface.

In the illustrated example, one or more input devices 722 are connectedto the interface circuit 720. The input device(s) 722 permit(s) a userto enter data and/or commands into the processor 712. The inputdevice(s) can be implemented by, for example, an audio sensor, amicrophone, a camera (still or video), a keyboard, a button, a mouse, atouchscreen, a track-pad, a trackball, isopoint and/or a voicerecognition system.

One or more output devices 724 are also connected to the interfacecircuit 720 of the illustrated example. The output devices 724 can beimplemented, for example, by display devices (e.g., a light emittingdiode (LED), an organic light emitting diode (OLED), a liquid crystaldisplay (LCD), a cathode ray tube display (CRT), an in-place switching(IPS) display, a touchscreen, etc.), a tactile output device, a printerand/or speaker. The interface circuit 720 of the illustrated example,thus, typically includes a graphics driver card, a graphics driver chipand/or a graphics driver processor.

The interface circuit 720 of the illustrated example also includes acommunication device such as a transmitter, a receiver, a transceiver, amodem, a residential gateway, a wireless access point, and/or a networkinterface to facilitate exchange of data with external machines (e.g.,computing devices of any kind) via a network 726. The communication canbe via, for example, an Ethernet connection, a digital subscriber line(DSL) connection, a telephone line connection, a coaxial cable system, asatellite system, a line-of-site wireless system, a cellular telephonesystem, etc.

The processor platform 700 of the illustrated example also includes oneor more mass storage devices 728 for storing software and/or data.Examples of such mass storage devices 728 include floppy disk drives,hard drive disks, compact disk drives, Blu-ray disk drives, redundantarray of independent disks (RAID) systems, and digital versatile disk(DVD) drives. In this example, the mass storage devices 728 implementsthe example signature scheme database 210.

The machine executable instructions 732 of FIGS. 4 and/or 5 may bestored in the mass storage device 728, in the volatile memory 714, inthe non-volatile memory 716, and/or on a removable non-transitorycomputer readable storage medium such as a CD or DVD.

FIG. 8 is a block diagram of an example processor platform 800structured to execute the instructions of FIG. 6 to implement the datacollection facility 118 of FIGS. 1 and/or 3. The processor platform 800can be, for example, a server, a personal computer, a workstation, aself-learning machine (e.g., a neural network), a mobile device (e.g., acell phone, a smart phone, a tablet such as an iPad™), a personaldigital assistant (PDA), an Internet appliance, a DVD player, a CDplayer, a digital video recorder, a Blu-ray player, a gaming console, apersonal video recorder, a set top box, a headset or other wearabledevice, or any other type of computing device.

The processor platform 800 of the illustrated example includes aprocessor 812. The processor 812 of the illustrated example is hardware.For example, the processor 812 can be implemented by one or moreintegrated circuits, logic circuits, microprocessors, GPUs, DSPs, orcontrollers from any desired family or manufacturer. The hardwareprocessor may be a semiconductor based (e.g., silicon based) device. Inthis example, the processor implements the example communicationsinterface 302, the example monitored signature analyzer 308, and theexample signature comparator 310.

The processor 812 of the illustrated example includes a local memory 813(e.g., a cache). The processor 812 of the illustrated example is incommunication with a main memory including a volatile memory 814 and anon-volatile memory 816 via a bus 818. The volatile memory 814 may beimplemented by Synchronous Dynamic Random Access Memory (SDRAM), DynamicRandom Access Memory (DRAM), RAMBUS® Dynamic Random Access Memory(RDRAM®) and/or any other type of random access memory device. Thenon-volatile memory 816 may be implemented by flash memory and/or anyother desired type of memory device. Access to the main memory 814, 816is controlled by a memory controller.

The processor platform 800 of the illustrated example also includes aninterface circuit 820. The interface circuit 820 may be implemented byany type of interface standard, such as an Ethernet interface, auniversal serial bus (USB), a Bluetooth® interface, a near fieldcommunication (NFC) interface, and/or a PCI express interface.

In the illustrated example, one or more input devices 822 are connectedto the interface circuit 820. The input device(s) 822 permit(s) a userto enter data and/or commands into the processor 812. The inputdevice(s) can be implemented by, for example, an audio sensor, amicrophone, a camera (still or video), a keyboard, a button, a mouse, atouchscreen, a track-pad, a trackball, isopoint and/or a voicerecognition system.

One or more output devices 824 are also connected to the interfacecircuit 820 of the illustrated example. The output devices 824 can beimplemented, for example, by display devices (e.g., a light emittingdiode (LED), an organic light emitting diode (OLED), a liquid crystaldisplay (LCD), a cathode ray tube display (CRT), an in-place switching(IPS) display, a touchscreen, etc.), a tactile output device, a printerand/or speaker. The interface circuit 820 of the illustrated example,thus, typically includes a graphics driver card, a graphics driver chipand/or a graphics driver processor.

The interface circuit 820 of the illustrated example also includes acommunication device such as a transmitter, a receiver, a transceiver, amodem, a residential gateway, a wireless access point, and/or a networkinterface to facilitate exchange of data with external machines (e.g.,computing devices of any kind) via a network 826. The communication canbe via, for example, an Ethernet connection, a digital subscriber line(DSL) connection, a telephone line connection, a coaxial cable system, asatellite system, a line-of-site wireless system, a cellular telephonesystem, etc.

The processor platform 800 of the illustrated example also includes oneor more mass storage devices 828 for storing software and/or data.Examples of such mass storage devices 828 include floppy disk drives,hard drive disks, compact disk drives, Blu-ray disk drives, redundantarray of independent disks (RAID) systems, and digital versatile disk(DVD) drives. In this example, the mass storage devices 828 implementsthe example audience measurement database 304, and the example referencesignature database 306.

The machine executable instructions 832 of FIG. 6 may be stored in themass storage device 828, in the volatile memory 814, in the non-volatilememory 816, and/or on a removable non-transitory computer readablestorage medium such as a CD or DVD.

From the foregoing, it will be appreciated that example methods,apparatus and articles of manufacture have been disclosed that enablethe collection of monitored signatures by audience measurement metersthat can be matched with corresponding references signatures with arelatively high degree of confidence. Reliable monitored signatures aregenerated in accordance with teachings disclosed herein by controllingthe operation of the audience measurement meter while generating thesignatures based on the circumstances associated with the media fromwhich the signatures are being taken. More particularly, the audiencemeasurement meter selects and applies a particular signature scheme(from a plurality of available schemes) that is adapted to the currentlydetected circumstances (including environmental conditions and/orcontent characteristics) of the monitored media. Dynamically selectingdifferent signature schemes that are specifically tailored to orotherwise yield a desired quality under different circumstances ensuresthat quality signatures are collected regardless of the situation. Whatis more, some disclosed examples further improve upon existing systemsby reducing processing requirements because only a single selectedsignature scheme needs to be used at any particular time and theselected scheme may be tailored with a payload that is no greater thanneeded to achieve the desired level of confidence in matching toreference signatures.

Example 1 includes an apparatus comprising a signature scheme selectorto select a first signature scheme from among a plurality of signatureschemes to generate monitored signatures for media being monitored by ameter, the first signature scheme selected based on a circumstanceassociated with the media, a signal generator to generate a firstmonitored signature from the media based on the first signature scheme,and a communications interface to transmit the first monitored signatureto a data collection facility.

Example 2 includes the apparatus as defined in example 1, wherein thecircumstance is based on an environmental condition associated with themedia.

Example 3 includes the apparatus as defined in example 2, wherein theenvironmental condition corresponds to an amount of background noise inan environment in which the media is monitored by the meter, thecircumstance corresponding to a first circumstance when the amount ofbackground noise is above a threshold, the circumstance corresponding toa second circumstance when the amount of background noise is below thethreshold.

Example 4 includes the apparatus as defined in example 3, furtherincluding a media content analyzer to detect watermarks encoded in themedia, and a media environment analyzer to determine the amount ofbackground noise based on the watermarks.

Example 5 includes the apparatus as defined in any one of examples 1-4,wherein the circumstance corresponds to a characteristic of an audiostream of the media.

Example 6 includes the apparatus as defined in example 5, furtherincluding a media content analyzer to measure signal energy of the audiostream of the media, wherein the circumstance corresponds to a firstcircumstance when a majority of the signal energy is in a firstfrequency range, and the circumstance corresponds to a secondcircumstance when a majority of the signal energy is in a secondfrequency range, the second frequency range being higher than the firstfrequency range.

Example 7 includes the apparatus as defined in any one of examples 5 or6, further including a media content analyzer to determine a genre ofthe media, wherein the circumstance corresponds to a first circumstancewhen the genre of the media is determined to be speech, and thecircumstance corresponds to a second circumstance when the genre of themedia is determined to be music.

Example 8 includes the apparatus as defined in any one of examples 1-7,wherein the signal generator generates a scheme identifier in connectionwith the first monitored signature, the scheme identifier indicating thefirst signature scheme was used to generate the first monitoredsignature.

Example 9 includes the apparatus as defined in any one of examples 1-8,wherein the signature scheme selector is to select a second signaturescheme from among the plurality of signature schemes based on a changein the circumstance associated with the media, the signal generator togenerate a second monitored signature from the media based on the secondsignature scheme, the communications interface to transmit the secondmonitored signature to the data collection facility.

Example 10 includes the apparatus as defined in example 9, wherein thesecond signature scheme is not used when the first monitored signatureis generated, and the first signature scheme is not used when the secondmonitored signature is generated.

Example 11 includes a non-transitory computer readable medium comprisinginstructions that, when executed, cause an audience measurement meter toat least select a first signature scheme from among a plurality ofsignature schemes to generate monitored signatures for media beingmonitored by the audience measurement meter, the first signature schemeselected based on a circumstance associated with the media, generate afirst monitored signature from the media based on the first signaturescheme, and transmit the first monitored signature to a data collectionfacility.

Example 12 includes the non-transitory computer readable medium asdefined in example 11, wherein the instructions further cause theaudience measurement meter to detect an amount of background noise in anenvironment in which the media is monitored by the audience measurementmeter, and determine the circumstance based on the amount of backgroundnoise.

Example 13 includes the non-transitory computer readable medium asdefined in example 12, wherein the instructions further cause theaudience measurement meter to detect watermarks encoded in the media,and determine the amount of background noise based on the watermarks.

Example 14 includes the non-transitory computer readable medium asdefined in any one of examples 11-13, wherein the instructions furthercause the audience measurement meter to determining a characteristic ofan audio stream of the media, and determining the circumstance based onthe characteristic.

Example 15 includes the non-transitory computer readable medium asdefined in example 14, wherein the characteristic corresponds to afrequency range containing a majority of signal energy of the audiostream.

Example 16 includes the non-transitory computer readable medium asdefined in any one of examples 11-15, wherein the instructions furthercause the audience measurement meter to generate a scheme identifier inconnection with the first monitored signature, the scheme identifierindicating the first signature scheme was used to generate the firstmonitored signature.

Example 17 includes the non-transitory computer readable medium asdefined in any one of examples 11-16, wherein the instructions furthercause the audience measurement meter to generate the first monitoredsignature based on the first signature scheme without implementing otherones of the plurality of signature schemes.

Example 18 includes a method comprising selecting, by executing aninstruction with a processor of a meter, a first signature scheme fromamong a plurality of signature schemes to generate monitored signaturesfor media being monitored by the meter, the first signature schemeselected based on a circumstance associated with the media, generating,by executing an instruction with the processor, a first monitoredsignature from the media based on the first signature scheme, andtransmitting, by executing an instruction with the processor, the firstmonitored signature to a data collection facility.

Example 19 includes the method as defined in example 18, furtherincluding detecting an amount of background noise in an environment inwhich the media is monitored by the meter, and determining thecircumstance based on the amount of background noise.

Example 20 includes the method as defined in any one of examples 18 or19, further including determining a characteristic of an audio stream ofthe media, and determining the circumstance based on the characteristic.

Although certain example methods, apparatus and articles of manufacturehave been disclosed herein, the scope of coverage of this patent is notlimited thereto. On the contrary, this patent covers all methods,apparatus and articles of manufacture fairly falling within the scope ofthe claims of this patent.

What is claimed is:
 1. An apparatus comprising: a signature schemeselector to select a first signature scheme from among a plurality ofsignature schemes to generate monitored signatures for media beingmonitored by a meter, the first signature scheme selected based on acircumstance associated with the media; a signature generator to:generate a first monitored signature from the media based on the firstsignature scheme; and generate a scheme identifier in connection withthe first monitored signature, the scheme identifier to specify that thefirst signature scheme was used to generate the first monitoredsignature, the scheme identifier including a first numeric identifierand a second numeric identifier, the first numeric identifier toidentify the first signature scheme, the second numeric identifier toidentify a configuration of the first signature scheme; and acommunications interface to transmit the first monitored signature andthe scheme identifier to a data collection facility.
 2. The apparatus asdefined in claim 1, wherein the circumstance is based on anenvironmental condition associated with the media.
 3. The apparatus asdefined in claim 2, wherein the environmental condition corresponds toan amount of background noise in an environment in which the media ismonitored by the meter, the circumstance corresponding to a firstcircumstance when the amount of background noise is above a threshold,the circumstance corresponding to a second circumstance when the amountof background noise is below the threshold.
 4. The apparatus as definedin claim 3, further including: a media content analyzer to detectwatermarks encoded in the media; and a media environment analyzer todetermine the amount of background noise based on the watermarks.
 5. Theapparatus as defined in claim 1, wherein the circumstance corresponds toa characteristic of an audio stream of the media.
 6. The apparatus asdefined in claim 5, further including a media content analyzer tomeasure signal energy of the audio stream of the media, wherein thecircumstance corresponds to a first circumstance when a majority of thesignal energy is in a first frequency range, and the circumstancecorresponds to a second circumstance when a majority of the signalenergy is in a second frequency range, the second frequency range beinghigher than the first frequency range.
 7. The apparatus as defined inclaim 5, further including a media content analyzer to determine a genreof the media, wherein the circumstance corresponds to a firstcircumstance when the genre of the media is determined to be speech, andthe circumstance corresponds to a second circumstance when the genre ofthe media is determined to be music.
 8. The apparatus as defined inclaim 1, wherein the signature scheme selector is to select a secondsignature scheme from among the plurality of signature schemes based ona change in the circumstance associated with the media, the signaturegenerator to generate a second monitored signature from the media basedon the second signature scheme, the communications interface to transmitthe second monitored signature to the data collection facility.
 9. Theapparatus as defined in claim 8, wherein the second signature scheme isnot used when the first monitored signature is generated, and the firstsignature scheme is not used when the second monitored signature isgenerated.
 10. A non-transitory computer readable medium comprisinginstructions that, when executed, cause an audience measurement meter toat least: select a first signature scheme from among a plurality ofsignature schemes to generate monitored signatures for media beingmonitored by the audience measurement meter, the first signature schemeselected based on a circumstance associated with the media; generate afirst monitored signature from the media based on the first signaturescheme; generate a scheme identifier in connection with the firstmonitored signature, the scheme identifier to specify that the firstsignature scheme was used to generate the first monitored signature, thescheme identifier including a first numeric identifier and a secondnumeric identifier, the first numeric identifier to identify the firstsignature scheme, the second numeric identifier to identify aconfiguration of the first signature scheme; and transmit the firstmonitored signature and the scheme identifier to a data collectionfacility.
 11. The non-transitory computer readable medium as defined inclaim 10, wherein the instructions further cause the audiencemeasurement meter to: detect an amount of background noise in anenvironment in which the media is monitored by the audience measurementmeter; and determine the circumstance based on the amount of backgroundnoise.
 12. The non-transitory computer readable medium as defined inclaim 11, wherein the instructions further cause the audiencemeasurement meter to: detect watermarks encoded in the media; anddetermine the amount of background noise based on the watermarks. 13.The non-transitory computer readable medium as defined in claim 10,wherein the instructions further cause the audience measurement meterto: determine a characteristic of an audio stream of the media; anddetermine the circumstance based on the characteristic.
 14. Thenon-transitory computer readable medium as defined in claim 13, whereinthe characteristic corresponds to a frequency range containing amajority of signal energy of the audio stream.
 15. The non-transitorycomputer readable medium as defined in claim 10, wherein theinstructions further cause the audience measurement meter to generatethe first monitored signature based on the first signature schemewithout implementing other ones of the plurality of signature schemes.16. A method comprising: selecting, by executing an instruction with aprocessor of a meter, a first signature scheme from among a plurality ofsignature schemes to generate monitored signatures for media beingmonitored by the meter, the first signature scheme selected based on acircumstance associated with the media; generating, by executing aninstruction with the processor, a first monitored signature from themedia based on the first signature scheme; generating, by executing aninstruction with the processor, a scheme identifier in connection withthe first monitored signature, the scheme identifier specifying that thefirst signature scheme was used to generate the first monitoredsignature, the scheme identifier including a first numeric identifierand a second numeric identifier, the first numeric identifier toidentify the first signature scheme, the second numeric identifier toidentify a configuration of the first signature scheme; andtransmitting, by executing an instruction with the processor, the firstmonitored signature and the scheme identifier to a data collectionfacility.
 17. The method as defined in claim 16, further including:detecting an amount of background noise in an environment in which themedia is monitored by the meter; and determining the circumstance basedon the amount of background noise.
 18. The method as defined in claim16, further including: determining a characteristic of an audio streamof the media; and determining the circumstance based on thecharacteristic.
 19. An apparatus comprising: a media content analyzer todetect a watermark encoded in media monitored by a meter; a mediaenvironment analyzer to: identify a baseline noise for the media basedon the watermark; and estimate an amount of background noise in anenvironment in which the media is monitored by the meter, the amount ofbackground noise estimated based on the baseline noise for the media; asignature scheme selector to select a first signature scheme from amonga plurality of signature schemes to generate monitored signatures forthe media, the first signature scheme selected based on the amount ofbackground noise; a signature generator to: generate a first monitoredsignature from the media based on the first signature scheme; andgenerate a scheme identifier in connection with the first monitoredsignature, the scheme identifier to specify that the first signaturescheme was used to generate the first monitored signature; and acommunications interface to transmit the first monitored signature andthe scheme identifier to a data collection facility.